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When students work with peers, they learn more actively, build richer knowledge structures, and connect material to their lives. However, not every peer learning experience online sees successful adoption. This paper articulates and addresses three adoption challenges for global-scale peer learning. First, peer interactions struggle to bootstrap critical mass. However, class incentives can signal importance and spur initial usage. Second, online classes have limited peer visibility and awareness, so students often feel alone even when surrounded by peers. We find that highlighting interdependence and strengthening norms can mitigate this issue. Third, teachers can readily access "big" aggregate data but not "thick" contextual data that helps build intuitions, so software should guide teachers' scaffolding of peer interactions. We illustrate these challenges through studying 8,500 students' usage of two peer learning platforms, Talkabout and PeerStudio. This paper measures efficacy through sign-up and participation rates and the structure and duration of student interactions.

Expert crowdsourcing (e.g., Upwork.com) provides promising benefits such as productivity improvements for employers, and flexible working arrangements for workers. Yet to realize these benefits, a key persistent challenge is effective hiring at scale. Current approaches, such as reputation systems and standardized competency tests, develop weaknesses such as score inflation over time, thus degrading market quality. This paper presents HirePeer, a novel alternative approach to hiring at scale that leverages peer assessment to elicit honest assessments of fellow workers' job application materials, which it then aggregates using an impartial ranking algorithm. This paper reports on three studies that investigate both the costs and the benefits to workers and employers of impartial peer-assessed hiring. We find, to solicit honest assessments, algorithms must be communicated in terms of their impartial effects. Second, in practice, peer assessment is highly accurate, and impartial rank aggregation algorithms incur a small accuracy cost for their impartiality guarantee. Third, workers report finding peer-assessed hiring useful for receiving targeted feedback on their job materials.

Online freelancing is growing rapidly. However, despite this rapid growth, we have a limited understanding of online freelancers' long-term experiences and evolution, or how online freelancing influences freelancers' broader career goals. To address this gap, we interviewed a set of online freelancers at two time periods, two and a half years apart. We found that long-term engagement with online freelancing involves a unique set of financial, emotional, relational, and reputational burdens that represent the overhead of maintaining an online freelancing career. We found that this overhead influenced online freelancers' participation and perceptions of online freelancing over time, as well as the strategies some freelancers employed to manage their careers. Our findings further highlight how online freelance platforms can afford unique career development opportunities over a longer period of time, including career exploration and transition, entrepreneurial training and reputation, and skills transfer. Based on our findings, we present policy and design implications to increase the sustainability and accessibility of online freelancing.

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